Expressive

rs10264306 - JAZF1-AS1

Magnitude 2.0 · 5 studies on file

Reported associations

  • A scalable variational inference approach for increased mixed-model association power - Nature genetics (2025) · Loya H, Kalantzis G, Cooper F, Palamara PF · PubMed 39789286

    ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%

  • A genetic map of human metabolism across the allele frequency spectrum - Nature genetics (2025) · Zoodsma M, Beuchel C, Yasmeen S, Kohleick L, Nepal A, Koprulu M, Kronenberg F, Mayr M, Williamson A, Pietzner M, Langenberg C · PubMed 41044249

    ABSTRACT: Genetic studies of human metabolism have been limited in scale and allelic breadth. Here we provide a data-driven map of the genetic regulation of circulating small molecules and lipoprotein characteristics (249 traits) measured using proton nuclear magnetic resonance spectroscopy across the allele frequency spectrum in ~450,000 individuals. Trans-ancestral meta-analyses identify 29,824 locus-metabolite associations mapping to 753 regions with effects largely consistent between men and women and large ancestral groups represented in UK Biobank. We observe and classify extreme genetic pleiotropy, identify regulators of lipid metabolism, and assign effector genes at >100 loci through rare-to-common allelic series. We propose roles for genes less established in metabolic control (

  • Integrative common and rare variant analyses provide insights into the genetic architecture of liver cirrhosis - Nature genetics (2024) · Ghouse J, Sveinbjörnsson G, Vujkovic M, Seidelin AS, Gellert-Kristensen H, Ahlberg G, Tragante V, Rand SA, Brancale J, Vilarinho S, Lundegaard PR, Sørensen E, Erikstrup C, Bruun MT, Jensen BA, Brunak S, Banasik K, Ullum H, Verweij N, Lotta L, Baras A, Mirshahi T, Carey DJ, Kaplan DE, Lynch J, Morgan T, Schwantes-An TH, Dochtermann DR, Pyarajan S, Tsao PS, Laisk T, Mägi R, Kozlitina J, Tybjærg-Hansen A, Jones D, Knowlton KU, Nadauld L, Ferkingstad E, Björnsson ES, Ulfarsson MO, Sturluson Á, Sulem P, Pedersen OB, Ostrowski SR, Gudbjartsson DF, Stefansson K, Olesen MS, Chang KM, Holm H, Bundgaard H, Stender S · PubMed 38632349

    ABSTRACT: We report a multi-ancestry genome-wide association study on liver cirrhosis and its associated endophenotypes, alanine aminotransferase (ALT) and γ-glutamyl transferase. Using data from 12 cohorts, including 18,265 cases with cirrhosis, 1,782,047 controls, up to 1 million individuals with liver function tests and a validation cohort of 21,689 cases and 617,729 controls, we identify and validate 14 risk associations for cirrhosis. Many variants are located near genes involved in hepatic lipid metabolism. One of these, PNPLA3 p.Ile148Met, interacts with alcohol intake, obesity and diabetes on the risk of cirrhosis and hepatocellular carcinoma (HCC). We develop a polygenic risk score that associates with the progression from cirrhosis to HCC. By focusing on prioritized genes from c

  • Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation - Nature human behaviour (2024) · Carey CE, Shafee R, Wedow R, Elliott A, Palmer DS, Compitello J, Kanai M, Abbott L, Schultz P, Karczewski KJ, Bryant SC, Cusick CM, Churchhouse C, Howrigan DP, King D, Davey Smith G, Neale BM, Walters RK, Robinson EB · PubMed 38965376

    ABSTRACT: Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and

  • Genetic diversity fuels gene discovery for tobacco and alcohol use - Nature (2023) · Saunders GRB, Wang X, Chen F, Jang SK, Liu M, Wang C, Gao S, Jiang Y, Khunsriraksakul C, Otto JM, Addison C, Akiyama M, Albert CM, Aliev F, Alonso A, Arnett DK, Ashley-Koch AE, Ashrani AA, Barnes KC, Barr RG, Bartz TM, Becker DM, Bielak LF, Benjamin EJ, Bis JC, Bjornsdottir G, Blangero J, Bleecker ER, Boardman JD, Boerwinkle E, Boomsma DI, Boorgula MP, Bowden DW, Brody JA, Cade BE, Chasman DI, Chavan S, Chen YI, Chen Z, Cheng I, Cho MH, Choquet H, Cole JW, Cornelis MC, Cucca F, Curran JE, de Andrade M, Dick DM, Docherty AR, Duggirala R, Eaton CB, Ehringer MA, Esko T, Faul JD, Fernandes Silva L, Fiorillo E, Fornage M, Freedman BI, Gabrielsen ME, Garrett ME, Gharib SA, Gieger C, Gillespie N, Glahn DC, Gordon SD, Gu CC, Gu D, Gudbjartsson DF, Guo X, Haessler J, Hall ME, Haller T, Harris KM, He J, Herd P, Hewitt JK, Hickie I, Hidalgo B, Hokanson JE, Hopfer C, Hottenga J, Hou L, Huang H, Hung YJ, Hunter DJ, Hveem K, Hwang SJ, Hwu CM, Iacono W, Irvin MR, Jee YH, Johnson EO, Joo YY, Jorgenson E, Justice AE, Kamatani Y, Kaplan RC, Kaprio J, Kardia SLR, Keller MC, Kelly TN, Kooperberg C, Korhonen T, Kraft P, Krauter K, Kuusisto J, Laakso M, Lasky-Su J, Lee WJ, Lee JJ, Levy D, Li L, Li K, Li Y, Lin K, Lind PA, Liu C, Lloyd-Jones DM, Lutz SM, Ma J, Mägi R, Manichaikul A, Martin NG, Mathur R, Matoba N, McArdle PF, McGue M, McQueen MB, Medland SE, Metspalu A, Meyers DA, Millwood IY, Mitchell BD, Mohlke KL, Moll M, Montasser ME, Morrison AC, Mulas A, Nielsen JB, North KE, Oelsner EC, Okada Y, Orrù V, Palmer ND, Palviainen T, Pandit A, Park SL, Peters U, Peters A, Peyser PA, Polderman TJC, Rafaels N, Redline S, Reed RM, Reiner AP, Rice JP, Rich SS, Richmond NE, Roan C, Rotter JI, Rueschman MN, Runarsdottir V, Saccone NL, Schwartz DA, Shadyab AH, Shi J, Shringarpure SS, Sicinski K, Skogholt AH, Smith JA, Smith NL, Sotoodehnia N, Stallings MC, Stefansson H, Stefansson K, Stitzel JA, Sun X, Syed M, Tal-Singer R, Taylor AE, Taylor KD, Telen MJ, Thai KK, Tiwari H, Turman C, Tyrfingsson T, Wall TL, Walters RG, Weir DR, Weiss ST, White WB, Whitfield JB, Wiggins KL, Willemsen G, Willer CJ, Winsvold BS, Xu H, Yanek LR, Yin J, Young KL, Young KA, Yu B, Zhao W, Zhou W, Zöllner S, Zuccolo L, Batini C, Bergen AW, Bierut LJ, David SP, Gagliano Taliun SA, Hancock DB, Jiang B, Munafò MR, Thorgeirsson TE, Liu DJ, Vrieze S · PubMed 36477530

    ABSTRACT: Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in s

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